Artificial neural network techniques to investigate potential interactions between biomarkers

Lemetre, C., 2010. Artificial neural network techniques to investigate potential interactions between biomarkers. PhD, Nottingham Trent University.

[img]
Preview
Text
203436_Christophe Lemetre PhD thesis.pdf

Download (14MB) | Preview

Abstract

High-throughput technologies in biomedical sciences, including gene microarrays, supposed to revolutionise the post-genomic era, have barely met the great expectations they inspired to the biomedical community at first. Current efforts are still focused toward improving the technology, its reproducibility and accuracy. In the meantime, computational techniques for the analysis of the data from these technologies have achieved great progresses and show encouraging results. New approaches have been developed to extract relevant information out from these results. However, important work needs to be further conducted in order to extract even more meaningful and relevant information. These techniques offer great possibilities to explore the overall dynamic held within a living organism. The potential information contained in their output can reveal important leads at deciphering the interconnection, interaction or regulation influences that can exist between several molecules. In front of an increasing interest of the scientific community toward the exploration of these dynamics, some groups have started to develop solutions based on different technologies to extract these information related to interactions. Here we present an Artificial Neural Network-based methodology for the study of interactions in gene transcriptomic data. This will be applied and validated in a breast cancer context.

Item Type: Thesis
Creators: Lemetre, C.
Date: 2010
Rights: This work is the intellectual property of the author and the Nottingham Trent University. You may copy up to 5% of this work for private study, or personal, non-commercial research. Any re-use of the information contained within this document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed in the first instance to the owner(s) of the Intellectual Property Rights.
Divisions: Schools > School of Science and Technology
Depositing User: EPrints Services
Date Added: 09 Oct 2015 09:34
Last Modified: 09 Oct 2015 09:34
URI: http://irep.ntu.ac.uk/id/eprint/142

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year